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Record W4400353914 · doi:10.1093/occmed/kqae023.0641

P-134 INVISIBLE OFFICE WORKERS’ DISEASES

2024· article· en· W4400353914 on OpenAlexaff
D Lahlou, Rim El Kholti, Abdeljalil El Kholti

Bibliographic record

VenueOccupational Medicine · 2024
Typearticle
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsEnvironmental healthMedicineOffice workersOccupational medicineOccupational exposureBusinessEngineeringOperations management

Abstract

fetched live from OpenAlex

Abstract Introduction Office workers are exposed to several risks that are often underestimated. Methods This study highlights the consequences linked to this exposure, through a retrospective study of data linked to office workers. Our investigation was carried out on a sample of 375 cases, following inclusion criteria: aged between 40 and 59 years, sedentary work in the office with exposure to the screen at least 4 hours/day. Results The average age of our study is 55.6, with a female predominance (a sex ratio of 0.41). According to the body mass index, we find 42% overweight, 39% having obesity, and only 18% have normal build. For the blood pressure, 59% had arterial hypertension, including only 32% with among them are followed by a doctor, 25% having high normal blood pressure of which 10% are followed, 8% having optimal blood pressure, and only 6.5% having normal blood pressure. Regarding visual acuity, 37% suffer from presbyopia, 9% have myopia, 35% have a combination of the two, 4% have astigmatism, and only 15% have normal visual acuity. For the diseases detected during medical visits or mentioned during the interview, we find 43% musculoskeletal disorders; 25% thyroid conditions, 21% psychological conditions and, 17% diabetes. Discussion These findings provide valuable insights into the health status of office workers, indicating a significant prevalence of various health conditions that require further medical attention and intervention. Conclusion Although the professional risks linked to office work are less visible, they aren’t absent, hence the need to apply effective preventive action in order to avoid the risks.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.513
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.335
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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